Abstract:BACKGROUND
Limited information is available about teenage pregnancy and childbearing in rural areas, even though approximately 20 percent of the nation’s youth live in rural areas. Identifying whether there are differences in the teenage birth rate (TBR) across metropolitan and nonmetropolitan areas is important, because these differences may reflect modifiable ecological-level influences such as education, employment, laws, healthcare infrastructure, and policies that could potentially reduce the TBR.
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“…4 may restrict its value to policy makers. Alternative methodologies have been used to investigate how relationships between adolescent motherhood and underlying determinants vary spatially [4, 39] and this offers opportunities for further analysis in low and middle income countries.Fig. 4Weighted level of education and first birth at less than 16 years old by province, Kenya DHS 2008…”
Background: Early adolescent pregnancy presents a major barrier to the health and wellbeing of young women and their children. Previous studies suggest geographic heterogeneity in adolescent births, with clear "hot spots" experiencing very high prevalence of teenage pregnancy. As the reduction of adolescent pregnancy is a priority in many countries, further detailed information of the geographical areas where they most commonly occur is of value to national and district level policy makers. The aim of this study is to develop a comprehensive assessment of the geographical distribution of adolescent first births in Uganda, Kenya and Tanzania using Demographic and Household (DHS) data using descriptive, spatial analysis and spatial modelling methods. Methods: The most recent Demographic and Health Surveys (DHS) among women aged 20 to 29 in Tanzania, Kenya, and Uganda were utilised. Analyses were carried out on first births occurring before the age of 20 years, but were disaggregated in to three age groups: <16, 16/17 and 18/19 years. In addition to basic descriptive choropleths, prevalence maps were created from the GPS-located cluster data utilising adaptive bandwidth kernel density estimates. To map adolescent first birth at district level with estimates of uncertainty, a Bayesian hierarchical regression modelling approach was used, employing the Integrated Nested Laplace Approximation (INLA) technique. Results: The findings show marked geographic heterogeneity among adolescent first births, particularly among those under 16 years. Disparities are greater in Kenya and Uganda than Tanzania. The INLA analysis which produces estimates from smaller areas suggest "pockets" of high prevalence of first births, with marked differences between neighbouring districts. Many of these high prevalence areas can be linked with underlying poverty. Conclusions: There is marked geographic heterogeneity in the prevalence of adolescent first births in East Africa, particularly in the youngest age groups. Geospatial techniques can identify these inequalities and provide policy-makers with the information needed to target areas of high prevalence and focus scarce resources where they are most needed.
“…4 may restrict its value to policy makers. Alternative methodologies have been used to investigate how relationships between adolescent motherhood and underlying determinants vary spatially [4, 39] and this offers opportunities for further analysis in low and middle income countries.Fig. 4Weighted level of education and first birth at less than 16 years old by province, Kenya DHS 2008…”
Background: Early adolescent pregnancy presents a major barrier to the health and wellbeing of young women and their children. Previous studies suggest geographic heterogeneity in adolescent births, with clear "hot spots" experiencing very high prevalence of teenage pregnancy. As the reduction of adolescent pregnancy is a priority in many countries, further detailed information of the geographical areas where they most commonly occur is of value to national and district level policy makers. The aim of this study is to develop a comprehensive assessment of the geographical distribution of adolescent first births in Uganda, Kenya and Tanzania using Demographic and Household (DHS) data using descriptive, spatial analysis and spatial modelling methods. Methods: The most recent Demographic and Health Surveys (DHS) among women aged 20 to 29 in Tanzania, Kenya, and Uganda were utilised. Analyses were carried out on first births occurring before the age of 20 years, but were disaggregated in to three age groups: <16, 16/17 and 18/19 years. In addition to basic descriptive choropleths, prevalence maps were created from the GPS-located cluster data utilising adaptive bandwidth kernel density estimates. To map adolescent first birth at district level with estimates of uncertainty, a Bayesian hierarchical regression modelling approach was used, employing the Integrated Nested Laplace Approximation (INLA) technique. Results: The findings show marked geographic heterogeneity among adolescent first births, particularly among those under 16 years. Disparities are greater in Kenya and Uganda than Tanzania. The INLA analysis which produces estimates from smaller areas suggest "pockets" of high prevalence of first births, with marked differences between neighbouring districts. Many of these high prevalence areas can be linked with underlying poverty. Conclusions: There is marked geographic heterogeneity in the prevalence of adolescent first births in East Africa, particularly in the youngest age groups. Geospatial techniques can identify these inequalities and provide policy-makers with the information needed to target areas of high prevalence and focus scarce resources where they are most needed.
“…Regional differences exist in adolescent development between urban and rural areas, demonstrated by variable pregnancy rates (Shoff & Yang, 2012) and patterns of adolescent substance use (Martino et al, 2008; Scaramella & Keyes, 2001), therefore onset experiences of these women may be unique based on their rural backgrounds. Additionally, it is possible that high rates of regional unemployment—9.4% in Appalachian Kentucky between 2010–2014 (Pollard & Jacobsen, 2016)—may have amplified the effect of unemployment on later risk behaviors.…”
Section: Discussionmentioning
confidence: 99%
“…Although it has been demonstrated that adolescents from rural areas are distinct in patterns of substance use (Martino, Ellickson, & McCaffrey, 2008; Scaramella & Keyes, 2001) and sexual behaviors (as suggested by teen birth rates; see Shoff & Yang, 2012) from those raised in urban environments, high-risk groups of rural women and girls are often overlooked in research contexts. In describing rural women’s initiation of risky behaviors and involvement with the justice system and exploring how those events are associated with differences in adult trajectories, this study will help to illustrate the development of these at-risk women and provide targeted guidance for gender-sensitive services in rural criminal justice settings.…”
Incarcerated women frequently report initiation of substance use and sexual encounters at an early age, and often engage in high-risk drug use and sexual behaviors as adults. This study examined the timing of first sex, drug use, and arrest, as well as their unique influences on specific risky behaviors in adulthood, among a high-risk population of rural women recruited from jails. Ages of initiation were all positively and significantly correlated, and each independently increased the likelihood of several risky behaviors in adulthood. Implications are discussed for screening, intervention, and treatment targeting high-risk women and girls in rural areas, particularly within criminal justice settings.
“…By using the GWR4 software to perform the analysis, we have adopted a split-GWR framework using data on just the high and very high social vulnerability communities. This approach has also been adopted by Shoff and Yang [51] while analysing the spatially varying predictors of teenage birth rates in metropolitan and non-metropolitan areas in the USA. GWR was originally developed for spatial point data analysis but it can also be applied to areal data by using the geographical centroids of the analysed areas [51].…”
This paper investigates local-scale social vulnerability to flood hazards in Romania, aiming to identify the most vulnerable social and demographic groups across a wide range of geographical locations by considering three dimensions: demographic, socioeconomic, and the built environment. The purpose of the paper is threefold: first, it strives to improve the Social Vulnerability model (SoVI®) by applying a different weighting method adapted to the Romanian context, taking into consideration the municipalities exposed to flood movements. Second, it aims to develop an assessment model for the most vulnerable communities by measuring the heterogeneity according to local indicators related to disaster risks. Third, it aims to facilitate emergency managers to identify community sub-groups that are more susceptible to loss and to increase the resilience of local communities. To perform local-level vulnerability mapping, 28 variables were selected and three aggregated indexes were constructed with the help of the ArcGIS software. Moreover, a model of Geographically Weighted Regression (GWR) between communities directly affected by floods and localities with high- and very high values of the Local Social Vulnerability Index (LoSoVI) was used to explore the spatial relationship among them and to compare the appropriateness of Ordinary Least Square (OLS) and GWR for such modelling. The established GWR model has revealed that the negative effects of flood hazards are often associated with communities with a high degree of social vulnerability. Thus, the analysis is able to provide a more comprehensive picture on communities in desperate need of financial resources in order to have the ability to diminish the negative impacts of flood hazards and to provide a more sustainable society.
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